1. Field of the Invention
The present invention relates to a method for converting a dimension of a vector, and more particularly, to a method for converting a dimension of a vector in waveform interpolation (WI) speech coding for converting elements of low and high frequency domains of a spectrum vector having a variable dimension into vectors having fixed dimensions, using only one codebook memory for slowly evolving waveform (SEW) spectrum vector quantization, such that each of the elements has different resolution from each other, thereby not only suppressing errors due to the vector dimension conversion but also effectively reducing codebook memory required for vector quantization.
2. Discussion of Related Art
In recent mobile communication systems, digital multimedia storage devices, and so forth, various kinds of speech coding algorithms have been frequently used in order to maintain the original sound quality of a speech signal with relatively few bits.
In general, a code excited linear prediction (CELP) algorithm is an effective coding method that maintains high sound quality even at a low bit rate of between 8 and 16 kbps.
An algebraic CELP coding method, which is one type of CELP coding method, is so successful that it has been adopted in many recent worldwide standards such as G.729, enhanced variable rate codec (EVRC), and adaptive multi-rate (AMR) vocoders.
However, according to the CELP algorithm, sound quality seriously deteriorates at a bit rate of under 4 kbps. Therefore, the CELP algorithm is known not to be appropriate in fields applying a low bit rate.
Meanwhile, WI speech coding is a speech coding method that guarantees good sound quality even at a low bit rate of below 4 kbps. According to the WI speech coding method, four parameters are extracted from an input speech signal, the four parameters being a linear prediction (LP) parameter, a pitch value, a power, and a characteristic waveform (CW).
Here, the CW parameter is divided again into two parameters of a slowly evolving waveform (SEW) and a rapidly evolving waveform (REW). Since the SEW parameter and the REW parameter have very different characteristics from each other, the two parameters are separately quantized to improve coding efficiency.
The SEW parameter is known to affect sound quality the most among the five parameters of a WI vocoder. Furthermore, a dimension of a SEW spectrum vector depends on a pitch period, and thus a variable dimension quantization method is required for SEW spectrum vector quantization.
However, a vector of the SEW variable dimension is hard to quantize by directly applying a conventional general quantization method, and thus a dimension conversion method is generally used for the variable dimension vector quantization.
In other words, when the vector dimension conversion method is used, the SEW spectrum vector can be quantized by applying the conventional general quantization method.
Meanwhile, the SEW parameter can be considered as the same kind of parameter as a harmonic magnitude vector in harmonic vocoders excluding WI vocoders.
Therefore, harmonic magnitude vector quantization in a WI vocoder and a harmonic vocoder requires harmonic vector dimension conversion in order to apply the conventional general quantization method in the same manner as the SEW parameter quantization mentioned above.